When an Icelander arrives at an office building and sees "Solarfri" posted, they need no further explanation for the empty premises: The word means "when staff get an unexpected afternoon off to enjoy good weather." The people of this rugged North Atlantic island settled by Norsemen some 1,100 years ago have a unique dialect of Old Norse that has adapted to life at the edge of the Artic. Hundslappadrifa, for example, means "heavy snowfall with large flakes occurring in calm wind." But the revered Icelandic language, seen by many as a source of identity and pride, is being undermined by the widespread use of English, both for mass tourism and in the voice-controlled artificial intelligence devices coming into vogue. Linguistics experts, studying the future of a language spoken by fewer than 400,000 people in an increasingly globalized world, wonder if this is the beginning of the end for the Icelandic tongue.

In this photo taken Saturday, April 15, 2017, Salome Sigurjonsdottir, 10, tests a voice-controlled television in an electronics store in Reykjavik. Sales assistant Einar Dadi said none of his TVs understood Icelandic. The revered Icelandic language, seen by many as a source of identity and pride, is being undermined by the widespread use of English both for mass tourism and in the voice-controlled artificial intelligence devices coming into vogue.

Lamenesses are frequently characterized by asymmetric limb motion, Bragança said. Strapped to different sections of a horse's body, inertial measurement units (IMUs) are becoming useful tools for evaluating asymmetry and body lean angles. Dutch and Belgian scientists are now looking at ways to gather reliable movement data from IMUs placed on horses' limbs, head, body, and pelvis. And this, they say, can lead to even greater accuracy in both veterinary diagnoses and performance evaluations. "It is important that we have methods to objectively quantify and record limb motion since we are now, more and more, aware of the limitations of the human eye as an instrument to detect motion asymmetries, especially at high speeds," said Filipe Serra Bragança, DVM, a PhD candidate in equine musculoskeletal biology at Utrecht University's Faculty of Veterinary Medicine Department of Equine Sciences, in The Netherlands.

Members of the British public are getting their first extended trial of a driverless shuttle bus. Over the next three weeks, about 100 people will travel in a prototype shuttle on a route in Greenwich, London. The vehicle, which travels up to 10mph (16.1kmph), will be controlled by a computer. However, there will be a trained person on board who can stop the shuttle if required during the tests. Oxbotica, the firm that developed the technology behind the shuttle, said 5,000 people had applied to take part. "Very few people have experienced an autonomous vehicle, so this is about letting people see one in person," chief executive Graeme Smith told the BBC.

Should you be worried about progress in Artificial Intelligence? Will Artificial Intelligence destroy jobs? Should we fear killer robots? Does Artificial Intelligence threaten our very existence? Artificial Intelligence (AI) is in the zeitgeist.

The notion of cars that drive themselves is one that becomes more and more real with each passing day. Acquisitions seem to be happening left and right, and almost every major auto manufacturer is devoting resources to bring us a self driving car. Companies like Google, Uber, and Tesla are all devoting significant investments to the self driving car with the universal target date of "2020" for commercialization being forecasted by nearly all of these players. Mobileye, about the only pure-play self driving car stock out there, recently announced a partnership with Delphi and a target date of 2019. While all eyes remain fixed on the big names in this game, there are some new entrants to this space that you may never heard of but that are getting closer and closer to making the self driving car a reality.

I am sure by now, you have heard the phrase that has been thrown around quite a lot by mostly, venture capitalists: "Artificial Intelligence (AI) is the new mobile." The reason why this phrase has been echoed in the tech industry is to emphasize that AI is not a short-lived fad, rather a revolution like mobile. More importantly, they seem to be right as in the last five years, giant tech companies have been pouring money into this technology. In fact, over 200 private companies using AI algorithms across different verticals have been acquired since 2012, with over 30 acquisitions taking place in Q1'17 alone. The acquisitions of AI startups are getting feisty, too.

Mark Curtis, Fjord co-founder and chief client officer – and Inspirefest 2016 speaker – tells us how design thinking can not only bring real human emotion into business, but it can also help forge the future of work. The world is changing at a pace we've not witnessed since the industrial revolution. With the added uncertainty of Brexit and global political turmoil, the future has never been less predictable, particularly for businesses that are so exposed to outside influence. But from challenge emanates great opportunity, and, with advancements in design, technology and even'contentious' artificial intelligence (AI), the workplace of the future is primed for disruption from within. So what do organisations need to do to future-proof themselves against these outside sociopolitical, economic and sometimes geographical challenges?

Michael Witbrock received his Ph.D. in Computer Science from Carnegie Mellon University, and is currently a distinguished research staff member at IBM T J Watson Research center, leading work at the intersection of learning and reasoning. Previously he Founded and acted as CEO at Curious Cat Company, building assistants that actually understand you and what you do, and was Vice President for Research at Cycorp, and CEO at Cycorp Europe, where he lead research in automated knowledge acquisition from text and dialogue, automated reasoning, and intelligent human-computer interaction. Previously to that he was Principal Scientist at Terra Lycos, working on integrating statistical and knowledge-based approaches to understanding web user behavior, a research scientist at Just Systems Pittsburgh Research Center, working on statistical text summarization, and a systems scientist at Carnegie Mellon on the Informedia spoken and video document information retrieval project. He is the author of numerous publications in areas ranging from neural networks, parallel computer architecture, multimedia information retrieval, web browser design, genetic design, computational linguistics and speech recognition, and is an inventor on seven US patents.

We study strictly proper scoring rules in the Reproducing Kernel Hilbert Space. We propose a general Kernel Scoring rule and associated Kernel Divergence. We consider conditions under which the Kernel Score is strictly proper. We then demonstrate that the Kernel Score includes the Maximum Mean Discrepancy as a special case. We also consider the connections between the Kernel Score and the minimum risk of a proper loss function. We show that the Kernel Score incorporates more information pertaining to the projected embedded distributions compared to the Maximum Mean Discrepancy. Finally, we show how to integrate the information provided from different Kernel Divergences, such as the proposed Bhattacharyya Kernel Divergence, using a one-class classifier for improved two-sample hypothesis testing results.